Senior AI-Ready Data Platform Engineer

CyberCube; United States; Remote; USD 150,000 - 210,000; Full time

Benefits offered by this job

Learning and development assistance

Vision and dental coverage

Extra vacation days during winter

Flexible working hours

Work-from-home option

Mentorship programs

Secondment programs

Work abroad up to 3 months with visa

AI Fluency at CyberCube

Job summary

CyberCube Analytics, Inc. is hiring a Senior Data Platform Engineer to own the architecture of the data layer feeding dashboards, apps, and AI agents across the business. You will design scalable, governed data access that is auditable and secure, enabling rapid analysis of sensitive portfolio data.

Our stack includes Python, GraphQL/Hasura, MySQL, Redis, Elasticsearch, Spark, Iceberg, Airflow, Redshift and AWS. You will shape data models, pipelines and AI interfaces across teams.

Qualifications

• Experience in data/backend engineering with strong Python and production API experience.
• Hands-on GraphQL design experience (Hasura a bonus).
• Relational DB skills on MySQL/PostgreSQL; schema design and indexing.
• Experience with Airflow and lakehouse tools (Spark, Iceberg, Redshift, Athena).
• Track record of authoring/reviewing system design docs.
• Real AI experience in engineering/data projects and daily AI tooling use.
• Knowledge of MCP servers or RAG pipelines is a plus.
• AI observability tooling (tokens, latency, failure modes).
• LangGraph/Claude Agent SDK/OpenAI Agents SDK familiarity desired.
• Guardrails and prompt-injection defense knowledge.
• Elasticsearch/OpenSearch experience.

Responsibilities

• Data as a product: set up contracts, versioning, docs, SLAs, and self-service onboarding for data access.
• Modelling & migration: design schemas for transactional/analytical access and migrate datasets.
• AI-facing interfaces: build tool definitions, scoped permissions, metadata exposure and audit trails.
• Agent vs. pipeline judgment: decide use-cases for automation vs deterministic pipelines and implement tooling.
• Platform health: improve scalability, reliability, and cost across Spark, Iceberg, Airflow and AWS.
• Governance: own data lineage, quality checks, and isolation for client-sensitive data.
• People & direction: write/review design docs and translate requirements into epics.

Skills

Data backend engineering

Python programming

GraphQL design

AI in engineering

System design documentation

API development

AI observability

RAG pipelines

LangGraph/Claude Agent SDK

AI tooling

ElasticSearch skills

Tools

Python

GraphQL (Hasura)

MySQL

PostgreSQL

Redis

Elasticsearch/OpenSearch

Spark

Iceberg

Airflow

Redshift

AWS

Job description

CyberCube Analytics, Inc. is hiring a Senior Data Platform Engineer to own the architecture of the data layer feeding dashboards, apps, and AI agents across the business. You will design scalable, governed data access that is auditable and secure, enabling rapid analysis of sensitive portfolio data.

Our stack includes Python, GraphQL/Hasura, MySQL, Redis, Elasticsearch, Spark, Iceberg, Airflow, Redshift and AWS. You will shape data models, pipelines and AI interfaces across teams.